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2011 Summer Training Course ESTIMATION THEORY Chapter 7 Maximum Likelihood Estimation

2011 Summer Training Course ESTIMATION THEORY Chapter 7 Maximum Likelihood Estimation

2011 Summer Training Course ESTIMATION THEORY Chapter 7 Maximum Likelihood Estimation. Outline. Why use MLE? How to find the MLE? Properties of MLE Numerical Determination of the MLE. Introduction.

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1.06k views • 75 slides
Semi-Automatic Content Extraction from Specifications

Semi-Automatic Content Extraction from Specifications

Semi-Automatic Content Extraction from Specifications. Krishnaprasad Thirunarayan Department of Computer Science & Engineering Wright State University Aaron Berkovich and Dan Sokol Cohesia Corporation. Extraction : Summarize in a prescribed vocabulary. Spec: Text. Spec: SDR.

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849 views • 66 slides
Semi-Automatic Content Extraction from Specifications

Semi-Automatic Content Extraction from Specifications

Semi-Automatic Content Extraction from Specifications. Krishnaprasad Thirunarayan Department of Computer Science & Engineering Wright State University Aaron Berkovich and Dan Sokol Cohesia Corporation. Extraction : Summarize in a prescribed vocabulary. Spec: Text. Spec: SDR.

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801 views • 66 slides
Visual motion

Visual motion

Visual motion. Many slides adapted from S. Seitz, R. Szeliski, M. Pollefeys. Motion and perceptual organization. Sometimes, motion is the only cue. Motion and perceptual organization. Sometimes, motion is the only cue. Motion and perceptual organization.

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469 views • 35 slides
Linearizing ODEs of a PID Controller

Linearizing ODEs of a PID Controller

Linearizing ODEs of a PID Controller. Anchored by: Rob Chockley and Scott Dombrowski. Basis for Linearization. Ordinary Differential Equation. Taylor Series Expansion. Linear Approximation. Real Life Example. For our example, we created a real world situation. In: 3 mol/s (const)

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294 views • 9 slides

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